A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning

The inertial measurement unit and ultra-wide band signal (IMU-UWB) combined indoor positioning system has a nonlinear state equation and a linear measurement equation. In order to improve the computational efficiency and the localization performance in terms of the estimation accuracy, the federated...

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Main Authors: Chengyang He, Chao Tang, Chengpu Yu
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/12/3514
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author Chengyang He
Chao Tang
Chengpu Yu
author_facet Chengyang He
Chao Tang
Chengpu Yu
author_sort Chengyang He
collection DOAJ
description The inertial measurement unit and ultra-wide band signal (IMU-UWB) combined indoor positioning system has a nonlinear state equation and a linear measurement equation. In order to improve the computational efficiency and the localization performance in terms of the estimation accuracy, the federated derivative cubature Kalman filtering (FDCKF) method is proposed by combining the traditional Kalman filtering and the cubature Kalman filtering. By implementing the proposed FDCKF method, the observations of the UWB and the IMU can be effectively fused; particularly, the IMU can be continuously calibrated by UWB so that it does not generate cumulative errors. Finally, the effectiveness of the proposed algorithm is demonstrated through numerical simulations, in which FDCKF was compared with the federated cubature Kalman filter (FCKF) and the federated unscented Kalman filter (FUKF), respectively.
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spelling doaj.art-3309da88d9f04ae7910202e149b0bdf32023-11-20T04:31:52ZengMDPI AGSensors1424-82202020-06-012012351410.3390/s20123514A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor PositioningChengyang He0Chao Tang1Chengpu Yu2School of Automation, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Automation, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Automation, Beijing Institute of Technology, Beijing 100081, ChinaThe inertial measurement unit and ultra-wide band signal (IMU-UWB) combined indoor positioning system has a nonlinear state equation and a linear measurement equation. In order to improve the computational efficiency and the localization performance in terms of the estimation accuracy, the federated derivative cubature Kalman filtering (FDCKF) method is proposed by combining the traditional Kalman filtering and the cubature Kalman filtering. By implementing the proposed FDCKF method, the observations of the UWB and the IMU can be effectively fused; particularly, the IMU can be continuously calibrated by UWB so that it does not generate cumulative errors. Finally, the effectiveness of the proposed algorithm is demonstrated through numerical simulations, in which FDCKF was compared with the federated cubature Kalman filter (FCKF) and the federated unscented Kalman filter (FUKF), respectively.https://www.mdpi.com/1424-8220/20/12/3514federated derivative cubature Kalman filteringinformation fusionindoor positioning
spellingShingle Chengyang He
Chao Tang
Chengpu Yu
A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
Sensors
federated derivative cubature Kalman filtering
information fusion
indoor positioning
title A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
title_full A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
title_fullStr A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
title_full_unstemmed A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
title_short A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
title_sort federated derivative cubature kalman filter for imu uwb indoor positioning
topic federated derivative cubature Kalman filtering
information fusion
indoor positioning
url https://www.mdpi.com/1424-8220/20/12/3514
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